The aim of I(eye)-Screen is to develop an artificial intelligence (AI)-based diagnostic decision support system for screening and monitoring of age-related macular degeneration (AMD) at an early stage before vision loss occurs. Late AMD is the leading cause of legal blindness >50 years with 110 mio individuals at risk. The multidisciplinary consortium brings together a network of clinical retina experts, computer scientists working at the cutting edge of AI development, an infrastructure of community-based opticians/optometrists and an SME experienced in digital platform performance to develop innovative and trustworthy AI tools for broad, real-time AMD screening and monitoring via a cloud-based infrastructure with unlimited access. To achieve the ambitious goal of finding “the needle in the haystack” in early AMD, Optical Coherence Tomography (OCT), a high-resolution, effortless imaging modality is used providing a detailed characterization of the retina in extensive volumetric scans. Breakthrough AI approaches for medical imaging will be developed to enable data-efficient and robust learning from sparse longitudinal OCT data to systematically analyse dense data volumes and identify (sub)clinical markers of disease activity. Clinical sites throughout Europe will collect a longitudinal cohort serving for calibrating and fine-tuning algorithms using the high-end OCT device available at eye clinics. Innovative AI technology will then be created to transfer the detection and monitoring tools to low-cost devices used in next door opticians’/optometrists’ offices. The timing of the project perfectly fits the recent regulatory approval of the first therapy to halt progression of the major atrophic type of AMD. The resulting AI-based “shared care” strategy offers unrestricted accessibility to vision-maintaining care with greatest health equity and provides a role model for screening for systemic, cardiovascular and neurodegenerative disease reflecting retinal biomarkers.

The main ambitions of the Solve-RD proposal are (i) to solve large numbers of RD, for which a molecular cause is not known yet, by sophisticated combined Omics approaches, and (ii) to improve diagnostics of RD patients through a “genetic knowledge web”. Solve-RD will pursue a clear visionary and integrated “beyond the exome” approach. The entire Solve-RD proposal has been motivated, designed and put together by a core group of four ERNs, but also reaches out to all 24 ERNs. To tackle diseases which are unsolved by applying cutting edge strategies, Solve-RD has thus formed a consortium that comprises (i) leading clinicians, geneticists and translational researchers of these ERNs, (ii) RD research and diagnostic infrastructures, (iii) patient organisations, as well as (iv) leading experts in the field of -omics technologies, bioinformatics and knowledge management. Solve-RD will deliver 7 main implementation steps: (i) Collect Phenotypes, (ii) New phenotype patterns, (iii) Re-analyse exomes / genomes, (iv) Novel molecular strategies, (v) Functional analysis, (iv) Clinical utility and (vii) Towards therapy. For analysis Solve-RD will apply data driven and expert driven approaches. We anticipate to increase diagnostic yield from 19.000 unsolved exomes/genomes by about 3-5%. Cohort specific innovative -omis strategies will be pursued, also addressing cost-effective issues. Analysis of more than 800 patients with highly peculiar (ultra-rare) phenotypes will highly increase the chance to find novel disease genes and novel disease mechanisms. We anticipate to solve more than 2.000 cases. Finding further matching patients will be secured by newly developed matchmaking approaches and by screening using MIPs technology in the more than 20.000 unclassified patients of the ERNs. For the first time in Europe we will also implement a novel brokerage structure connecting clinicians, gene discoverer and basic researcher to quickly verify novel genes and disease mechanisms.

In most developed countries, the proportion of elderly people in the population is growing rapidly and approaching the elderly market represents a key issue. The global population aged 60 years and older has doubled since 1980 and will probably reach two billion by 2050. In Europe counts 17% of the population is 65 years old or older and 4.7% 80 years old or older. The population of elderly people in Europe is increasing rapidly and in 2060 nearly 30% will be over 65 years old, and 12% over 80. Developing age-friendly products and services for this target group is an absolute necessity for facing the specific health challenges of the 21st century, caused by population ageing. The question of the needs of elderly people in term of food products with optimized nutritional and sensory values in order to permit longer life and better ageing without deficiencies is therefore of crucial importance. The ambition of AlimaSSenS is to address this issue by gathering food industry representatives and scientists in a strong combined research effort with a focus on Food Oral Processing (FOP) efficiency in the elderly. AlimaSSenS is a large and highly integrated project whose main objective is to develop and offer at the end food products, that are as appropriate as possible for the FOP abilities of elderly people living at home while retaining both ease of eating and eating pleasure and high nutritional value. In particular, AlimaSSenS aims at (1) understanding the impact of changes in oral status with age on food oral processing and their consequences on ease of eating & eating pleasure and bio-accessibility of nutrients using in vivo, in vitro & in silico approaches (2) developing food products adapted to the food oral processing efficiencies of the elderly and still considering meal and purchase practices of this population. Three types of food product are being investigated (meat, cereals and dairy products). To reach its objectives, AlimaSSenS proposes a multidisciplinary approach associating expertise in odontology, physiology, sensory evaluation, consumer behaviour, nutrition, epidemiology, data mining, food process, sociology and economy. It is a four year project divided into 4 phases: The first phase consists of setting up panels & methodologies (including FOP related sensory profile) and the choice of food matrix to be developed The second phase consists of (i) the development of novel food products using iterative approaches involving input from food processing and structure including data-mining, sensory data, FOP, bioavailability and bio-accessibility, food industrial partners (ii) characterization of elderly population in terms of food choice, food consumption, culinary and purchasing practices. The third phase consists of experimental economics of the novel food products to be released. The last phase is devoted to the dissemination and valorisation of the results AlimaSSenS is a public-private collaborative research project involving 10 academic and 4 industrial partners and a network of technical centres represented by 1 technical centre. AlimaSSenS is thus presented as an industrial-academic partnership project.

Methods of estimation of additional mortality due to cancer aim at estimating and modelling the excess mortality to which a studied group of patient's cancer is subjected and at estimating their relative survival (i.e. the survival corrected for all the other causes of death). In this context, the objective of the modelling is to estimate the impact of prognostic factors on the excess mortality risk and to assess the cure rate in different subgroups of patients. These methods are used in order to produce statistics concerning survival of patients with cancer, estimated from population-based data collected by cancer registries. In France, population-based cancer registration is carried out on a Departmental level. These registries are grouped together in the FRANCIM network, for which one of the topic of its research program in cancer epidemiology focus on the estimation of the survival of cancer's patients in France. In order to achieve this, data of cancer registries have been pooled in a common database localised in the Service de Biostatistiques des Hospices Civils de Lyon. These statistics are analysed regularly and published by the different European countries and comparisons between countries are justified only if the methods used for that have taken into account bias relative of observational studies and if they are the result of a thought and a strategy adopted by all the partners. The development and the homogenisation of such methodology are totally justified in this context. The objective of this project is to provide a more complete set of analytic tools to estimate cancer survival and to assess the public health implications of these estimates. The research will produce a range of new clinical and public health insights from cancer survival data. We propose to explore and to address two complementary themes: - Improvements in cancer relative survival analysis methodology: extension of methods developed for censored data to the framework of relative survival analysis; - Creation of a 'standardized' approach for estimating cancer survival in France, or even in Europe, using Registry data. This project will allow for the creation of a network including 5 French partners, having complementarities and experience in the framework of the analysis of mortality due to cancer and the development of statistical methods. Two European partners and one Canadian, internationally known, will participate to this project as external members. The project is divided into 3 work packages: WP1: Comparison of the actual methods used to estimate relative survival WP2: Extension and development of statistical methods used to estimate relative survival. This necessitate (i) statistical researches to deal with the important remaining issues, and (ii) to develop statistical programs to perform relative survival analyses using approaches studied and developed in this project. WP3: Production of guidelines for cancer survival analysis with population-based data, answering to public health considerations The performances of the estimators of these new models will be assessed by simulations. Applications based on real data will be used to illustrate these new approaches and for the elaboration of guidelines. Data will be provided by some French cancer registries and by our European partners. Specific works are defined for each partner who will produce specific deliverables. If the project goes on well, it will allow to propose an adapted methodology in order to obtain correct estimates of the excess mortality due to cancer and to its determinants. This methodological approach is a preliminary condition for a rational management of such disease, on its medical and socio-economic aspects, that will be obtained from registries data.